eMoT treats reasoning trajectories as dynamic memories with corrosion, symbolic Python anchoring, and consistency refinement, raising accuracy on Game of 24 to 100% and improving math benchmarks over CoT baselines with a lightweight model.
Graph-augmented reasoning: Evolving step-by-step knowledge graph retrieval for llm reasoning.arXiv preprint arXiv:2503.01642, 2025
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eMoT: evolving Memory-of-Thought via Symbolic Anchoring and Memory Corrosion
eMoT treats reasoning trajectories as dynamic memories with corrosion, symbolic Python anchoring, and consistency refinement, raising accuracy on Game of 24 to 100% and improving math benchmarks over CoT baselines with a lightweight model.